import numpy as np
df = h2o.H2OFrame.from_python(np.random.randn(100,4).tolist(), column_names=list('ABCD'))

# View top 10 rows of the H2OFrame
df.head()

#         A           B           C          D
# ---------  ----------  ----------  ---------
# -0.613035  -0.425327   -1.92774    -2.1201
# -1.26552   -0.241526   -0.0445104   1.90628
#  0.763851   0.0391609  -0.500049    0.355561
# -1.24842    0.912686   -0.61146     1.94607
#  2.1058    -1.83995     0.453875   -1.69911
#  1.7635     0.573736   -0.309663   -1.51131
# -0.781973   0.051883   -0.403075    0.569406
#  1.40085    1.91999     0.514212   -1.47146
# -0.746025  -0.632182    1.27455    -1.35006
# -1.12065    0.374212    0.232229   -0.602646
# 
# [10 rows x 4 columns]

# View bottom 5 rows of the H2OFrame
df.tail(5)

#         A           B          C          D
# ---------  ----------  ---------  ---------
#  1.00098   -1.43183    -0.322068   0.374401
#  1.16553   -1.23383    -1.71742    1.01035
# -1.62351   -1.13907     2.1242    -0.275453
# -0.479005  -0.0048988   0.224583   0.219037
# -0.74103    1.13485     0.732951   1.70306
# 
# [5 rows x 4 columns]